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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,351 records · Page 75

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DOE OSTI2017

Development of High Temperature Out-of-Pile Experiments for Testing Nuclear Thermal Propulsion Fuel Surrogates

Nuclear thermal propulsion (NTP) technology is designed to provide “in-space” vehicle propulsion by deriving thrust from a hydrogen working fluid that is heated from a nuclear reaction. Initial NTP fuel structures (primarily carbon/carbide based materials) developed by the Rover/NERVA program were designed to withstand temperatures exceeding 2400 K and remain intact after tens of firing cycles. Current programs responsible for development of this technology expect the fuels to withstand temperatures in excess of 2550K under a similar duty cycle. Experiments that subject fuels to these conditions are being developed to provide data and performance information for optimization and potential down-selection of the candidate materials. Initial tests will be designed for laboratory benchtop operation and will not expose surrogate specimens to the hydrogen working fluid or irradiation fields. The primary focus of these out-of-pile experiments will be to study thermal performance and thermal failure limits of the candidate specimen materials.

Howard, Richard↗

DOE OSTI2016

Full-duplex ultrasonic through-wall communication and power delivery system with frequency tracking

A method and apparatus provide simultaneous bi-directional communications through a barrier using a pair of piezoelectric transducers. Outside-to-inside transmission of differentially encoded binary data is only sampled at the inside when a known repeated bit in a Barker sequence is transmitted in the other direction. Differentially encoded data is translated based on the absolute value of differences between each signal envelope sample and the previous signal envelope sample. Inside-to-outside data is transmitted by varying an electrical load on the inside transducer to vary the proportion of a continuous wave signal it reflects. The reflected portion of the continuous wave changes the electrical impedance of the outside transducer and this change is measured and interpreted as binary data. Two frequency selection algorithms select minimally sufficient and then optimal frequencies for power and data transmission by a frequency stepping process.

Lawry, Tristan J.↗

DOE OSTI2023

Systems and methods for hierarchical multi-objective optimization

A method for optimizing objective functions can include selecting an objective function based at least on a hierarchy, applying parameters to the objective function to generate an output, responsive to the output not satisfying a tolerance condition, assigning a penalty to the set of parameters and evaluating a convergence condition using the set of parameters and the penalty, responsive to the output satisfying the tolerance condition, evaluating an additional objective function using the parameters in an order corresponding to the hierarchy or evaluating the convergence condition responsive to the selected objective function being a final objective function, modifying the set of parameters using a genetic algorithm responsive to the set of parameters not satisfying the convergence condition, and outputting the set of parameters responsive to the set of parameters satisfying the convergence condition.

Chan, Henry↗

DOE OSTI2024

Ensemble variational Fokker-Planck methods for data assimilation

Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space under the flow of an McKean-Vlasov-Itˆo process. This work introduces the Variational Fokker-Planck (VFP) framework for data assimilation, a general approach that includes previously known particle flow filters as special cases. The McKean-Vlasov-Itˆo process that transforms particles is defined via an optimal drift that depends on the selected diffusion term. It is established that the underlying probability density - sampled by the ensemble of particles - converges to the Bayesian posterior probability density. For a finite number of particles the optimal drift contains a regularization term that nudges particles toward becoming independent random variables. Based on this analysis, we derive computationally-feasible approximate regularization approaches that penalize the mutual information between pairs of particles, and avoid particle collapse. Moreover, the diffusion plays a role akin to a particle rejuvenation approach that aims to alleviate particle collapse. The VFP framework is very flexible. Different assumptions on prior and intermediate probability distributions can be used to implement the optimal drift, and localization and covariance shrinkage can be applied to alleviate the curse of dimensionality. A robust implicit-explicit method is discussed for the efficient integration of stiff McKean- Vlasov-Itˆo processes. Here, the effectiveness of the VFP framework is demonstrated on three progressively more challenging test problems, namely the Lorenz ’63, Lorenz ’96 and the quasi-geostrophic equations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Simplified Two-Stage Model Predictive Control for a Hybrid Multilevel Converter With Floating H-Bridge

This paper proposes a simplified two-stage model predictive control (ST-MPC) for a hybrid multilevel converter, which is an active-neutral-point-clamped converter with floating H-bridge (ANPC-H). The objective of the first stage is to select the voltage vector that has the optimal current tracking performance by using a novel geometrical positioning approach in the complex plane. The second stage selects the best switching state among all the available switching states that belong to the same voltage vector obtained in the first stage, to balance dc capacitor voltages and reduce the common mode voltage. The proposed ST-MPC can dramatically reduce the computational burden and ensure the best current tracking by the two-stage structure, such that the execution time is much shorter compared with the conventional MPC. In addition, the geometrical positioning approach in the first stage is generic and can be applicable for any multilevel converters with N-level output; thus, this ST-MPC can be applied for both sevenand nine-level operation of the hybrid ANPC-H converter under different dc voltage ratios. Both simulation results and experimental results obtained on a silicon carbide hybrid ANPC-H converter prototype validate the feasibility and effectiveness of the proposed ST-MPC strategy.

42 ENGINEERING↗

NASA NTRS1982

Nuclear electric propulsion mission to Neptune

A nuclear electric propulsion (NEP) mission to Neptune is studied. Results of trajectory and propulsion parameter optimization are presented which lead to a selection of key electric propulsion system parameters. Spiral earth escape and spiral capture modes are assumed in the optimization studies. Flight time vs payload for Space Transportation System (STS)/Centaur injection and Triton-aided orbit capture at Neptune are also briefly investigated as methods of improving mission performance. Radiation effects of the earth spiral phase are discussed. The effects of NEP technology on science payloads and mission and system designs are evaluated. NEP is shown to be a very flexible and high performing propulsion technology.

Nock, K. T.↗

NASA NTRS2023

Additive Manufacturing Process Development DOE for NASA HR-1 using Laser Blown Powder Directed Energy Deposition

NASA HR-1 is a Fe-Ni-Cr alloy that is used for high pressure hydrogen applications such as rocket engines, energy, and oil and gas. This investigation was focused on conducting a design of experiment program aimed at mapping the parameter process window for NASA HR-1 using the laser blown powder directed energy deposition (LP-DED) process. A two phased design of experiments (DOE), the first phase of the experiment was focused on optimizing single bead tracks while the second phase of the experiment was focused on optimizing bead overlap hatching in a multi pass bead build up. During the first phase of the deposition parameters, namely laser power, travel speed, and powder feed rate were varied. A down selection from the single bead parameter set was made and hatching experiments were conducted that focused on the overlap distance. In this paper the approach for conducting the DOE and results are discussed. The results focused on measurement of bead geometry, the as-built microstructural evolution, and porosity within the samples. The team at MSFC saw a variety of results across the process map created during the first phase of experimentation and were able to down select a parameter that created an optimal bead shape with a minimal amount of build porosity. It was determined that laser power and robot travel speed were the most sensitive parameters. The results from this investigation will inform future laser powder directed energy deposition parameter developments.

Parker Shake↗

DOE OSTI2026

Trends and limits of CO 2 capture in solid and liquid sorbents at standard conditions

Carbon capture and storage (CCS) plays a critical role in achieving climate change mitigation targets, offering a pathway to decarbonize power generation, industrial processes, and heat production while addressing atmospheric CO 2 removal. While CCS technologies are technically advanced, the widespread adoption of 100 % CO 2 capture capacities such as 1 mol of CO 2 /mol of material and 1 g CO 2 /g storage (targeted by the DARPA, Defense Sciences Office, USA Govt.) has raised questions about the feasibility of achieving higher capture capacities. In the context of limiting global warming to 1.5°C, reaching 100 % CO 2 capture capacity is increasingly necessary, with residual emissions requiring complementary carbon dioxide removal (CDR) technologies. This review exclusively focuses on the CO 2 capture capacities of various sorbents under standard conditions, using different evaluation metrics. This study explores the performance of solid and liquid sorbents under standard conditions, analyzing factors including surface area, pore structure, solvent type, and functionalization to identify materials optimized for industrial-scale CCS applications. Emerging sorbents, including ILs, MOFs, COFs, POPs, DES, RCC, hybrid materials, and reactive sorbents, offer significant potential for enhanced selectivity and energy-efficient regeneration. Through a systematic assessment of gravimetric, volumetric, and molar capacities, the study provides insights into material efficiencies and trade-offs, offering guidance on optimizing sorbent selection for specific applications. The research advances understanding of scalable CCS technologies, contributing to global efforts to achieve net-zero emissions and address the pressing challenge of climate change.

Absorption↗

DOE OSTI2019

Bayesian modeling of inconsistent plastic response due to material variability

The advent of fabrication techniques such as additive manufacturing has focused attention on the considerable variability of material response due to defects and other microstructural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. To account for material response variability through variations in physical parameters, we adapt a recent Bayesian embedded modeling error calibration technique. We use Bayesian model selection to determine the most plausible of a variety of plasticity models and the optimal embedding of parameter variability. To expedite model selection, we develop an adaptive importance-sampling-based numerical integration scheme to compute the Bayesian model evidence. In conclusion, we demonstrate that the new framework provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.

36 MATERIALS SCIENCE↗

DOE OSTI2017

CYCLE MODELING AND OPTIMIZATION OF AN INTEGRALLY GEARED sCO2 COMPANDER

This paper presents the selection of a system configuration and off-design control method for an integrally geared compander based on cycle modeling and optimization. The goal of the cycle modeling was to determine a cycle configuration that would reach an efficiency of 50% at design conditions and to optimize off-design control to maintain high efficiencies. The compander is being developed for use in a concentrated solar power supercritical carbon dioxide power plant with expected turbine inlet temperatures of 705°C and utilizing dry cooling leading to compressor inlet temperature varying between 35°C and 55°C. The compander is unique as it consists of eight turbomachinery stages on four pinions all being driven by a single bull gear. The separate stages offer the opportunity to consider a variety of flow splits and cycle configurations including intercooling and multiple stages of reheat. Cycle modeling was conducted in two stages: on-design and off-design. On-design modeling was simulated with all components operating at their design point. This was used to compare the performance of different cycle configurations and design temperatures. Off-design modeling was then performed to investigate the temperature dependence of the cycle efficiency and power output and to develop a control strategy. Strategies considered and discussed include: turbine bypass, compressor recycle, inlet guide vanes, and inventory control. To determine the best operating conditions for each configuration and control strategy, a genetic algorithm was implemented to optimize the cycle performance across the range of operating temperatures being considered. The final selection of cycle configuration, design temperature and control strategy is also presented.

bennett, jeffrey↗

NASA NTRS1986

CSTAR star catalogue development

The Continuous Stellar Tracking Attitude Reference (CSTAR) system is an in-house project for the Space Station to provide high accuracy, drift free attitude and angular rate information for the GN&C system. Constraints exist on the star catalogue incorporated in the system. These constraints include the following: mass memory allocated for catalogue storage, star tracker imaging sensitivity, the minimum resolvable separation angle between stars, the width of the field of view of the star tracker, and the desired number of stars to be tracked in a field of view. The Smithsonian Astrophysical Observatory (SAO) catalogue is the basis reference for this study. As it stands, the SAO does not meet the requirements of any of the above constraints. Star selection algorithms have been devised for catalogue optimization. Star distribution statistics have been obtained to aid in the development of these rules. VAX based software has been developed to implement the star selection algorithms. The software is modular and provides a design tool to tailor the catalogue to available star tracker technology. The SAO catalogue has been optimized for the requirements of the present CSTAR system.

Uhde-Lacovara, J. A.↗

DOE OSTI2019

Ideal isotropic auxetic networks from random networks

We design and create isotropically auxetic networks with Poisson's ratio close to −1 in experiments. To achieve this, we selectively prune bonds from disordered networks, and then optimize the properties of individual bonds and nodes.

Reid, Daniel R.↗

DOE OSTI2018

Current capabilities of the residual stress diffractometer at the high flux isotope reactor

The engineering diffractometer 2nd Generation Neutron Residual Stress Facility (NRSF2) at the Oak Ridge National Laboratory’s High Flux Isotope Reactor was built specifically for the mapping of residual strains. NRSF2 is optimized to investigate a wide range of engineering materials by providing the user a selection of monochromatic neutron wavelengths to maintain the selected Bragg reflection near 2θ = 90°, which is the optimal scattering geometry for strain mapping. Here in this work, details of the instrument configuration and operation are presented, and considerations for experimental planning are also discussed. Selected examples of recent residual stress work completed with NRSF2 are presented to highlight capabilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Objective and algorithm considerations when optimizing the number and placement of turbines in a wind power plant

Abstract. Optimizing turbine layout is a challenging problem that has been extensively researched in the literature. However, optimizing the number of turbines within a given boundary has not been studied as extensively and is a difficult problem because it introduces discrete design variables and a discontinuous design space. An essential step in performing wind power plant layout optimization is to define the objective function, or value, that is used to express what is valuable to a wind power plant developer, such as annual energy production, cost of energy, or profit. In this paper, we demonstrate the importance of selecting the appropriate objective function when optimizing a wind power plant in a land-constrained site. We optimized several different wind power plants with different wind resources and boundary sizes. Results show that the optimal number of turbines varies drastically depending on the objective function. For a simple, one-dimensional, land-based scenario, we found that a wind power plant optimized for minimal cost of energy produced just 72 % of the profit compared to the wind power plant optimized for maximum profit, which corresponded to a loss of about USD 2 million each year. This paper also compares the performance of several different optimization algorithms, including a novel repeated-sweep algorithm that we developed. We found that the performance of each algorithm depended on the number of design variables in the problem as well as the objective function.

17 WIND ENERGY↗

DOE OSTI2023

A Comparative Study of Electrical Double Layer Effects for CO Reduction Reaction Kinetics

Solvation models describe how the interactions between the solutes and solvents affect the reactivity and selectivity in electrochemical processes. In this study, we developed a framework for evaluating the effects of applied potential and electrical double layer on CO reduction (COR), comparing fully explicit, implicit, and hybrid solvation models at the standard hydrogen electrode (SHE) scale. We analyzed all crucial intermediates leading to the production of C 1 and C 2 products and found good agreement across these models. Some notable differences were observed in the implicit description of *C and *CO adsorption at higher overpotentials and overall trends in the adsorption energies within the hybrid model. Using this unified SHE framework, we built comparable microkinetic models for COR kinetics and rates. Despite small differences in thermodynamics, solvation-model-based microkinetic simulations showed good agreement for onset potentials against the benchmark experiment. Only qualitative difference was observed for C 1+ versus hydrogen evolution at high overpotentials for the implicit model. Finally, we constructed a generalized C 2 selectivity map in descriptor space (U SHE , ΔG electrolyte CO ), which highlights the limitations of a copper-based COR catalyst and guides the search for optimal descriptor parameters to maximize C 2 selectivity. In conclusion, these findings demonstrate the importance of considering electrical double layer effects in reduction reactions and offer a useful framework for comparing solvation models and predicting optimal electrochemical conditions for specific applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

In Vitro Selection of Antibodies Targeting Yersinia pestis Membrane Lipids Using Nanodisc-Based Antigen Presentation

Proteins are the most common targets for antibody discovery and vaccine development, but their sequence variability can limit the breadth of resulting antigens. Lipids represent an alternative class of antigens due to their structural conservation and roles in host–pathogen interactions. Here, we describe the development and optimization of an in vitro antibody selection workflow using lipid-containing nanodiscs as antigen presentation platforms to enable phage and yeast display selections under conditions adapted for these non-protein targets. Lipopolysaccharide (LPS) nanodiscs were first used as a model system to evaluate selection strategies, including competitive and subtractive approaches to reduce non-specific binders, yielding peptide and single-chain variable fragment (scFv) binders that were affinity matured to improve binding signals. The same approach was subsequently used to select scFv antibodies that recognize lipid nanodiscs prepared from Yersinia pestis membrane lipid extracts. These antibodies show binding to lipid nanodiscs derived from Y. pestis, with evidence of selectivity relative to control nanodiscs. Overall, this work establishes a workflow for antibody selection against lipid-containing nanodisc antigens and highlights practical considerations associated with these targets. The approach may be useful for generating affinity reagents to membrane-associated lipids, although further characterization is required to define antigen specificity and functional activity.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1982

A study of the selection of microcomputer architectures to automate planetary spacecraft power systems

Performance and reliability models of alternate microcomputer architectures as a methodology for optimizing system design were examined. A methodology for selecting an optimum microcomputer architecture for autonomous operation of planetary spacecraft power systems was developed. Various microcomputer system architectures are analyzed to determine their application to spacecraft power systems. It is suggested that no standardization formula or common set of guidelines exists which provides an optimum configuration for a given set of specifications.

Nauda, A.↗

NASA NTRS1984

Design of an optimal output feedback control system with modal insensitivity

This paper deals with the design of an output feedback controller which results in selected modal insensitivity, and at the same time optimizes a quadratic performance index representative of desired system performance for nominal plant parameter values. The approach taken here is to characterize the class of attainable eigenvectors for a given set of eigenvalues (distinct or non-distinct) which lie in a subspace called the 'Modal Insensitivity Subspace'. A constraint is established on the feedback matrix which results in modal insensitivity. Necessary conditions for optimality subject to the constraint on the feedback matrix are given. This forms the basis for a numerical algorithm to compute the optimal feedback gain which analyzed for convergence. To illustrate the procedure, a design is carried out using the lateral dynamics of an L-1011 aircraft.

Raman, K. V.↗